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  1. 381

    Employee loyalty evaluation using machine learning in technology-based small and medium-sized enterprises by Yong Shi, Yuan Wang, Hongkun zuo

    Published 2025-07-01
    “…Through several machine learning models and algorithms to predict employee loyalty, the feasibility of machine learning to predict employee loyalty is proved, and the evaluation of talent in TSMEs is supported by decision analysis. …”
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    Article
  2. 382

    Dimensional Accuracy Evaluation of Single-Layer Prints in Direct Ink Writing Based on Machine Vision by Yongqiang Tu, Haoran Zhang, Hu Chen, Baohua Bao, Canmi Fang, Hao Wu, Xinkai Chen, Alaa Hassan, Hakim Boudaoud

    Published 2025-04-01
    “…Process parameter optimization experiments validated the system’s effectiveness, showing at least 76.3% enhancement in printed layer dimensional accuracy. This non-contact evaluation solution establishes a robust framework for quantitative quality control in DIW applications, providing critical insights for process optimization and standardization efforts in additive manufacturing.…”
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    Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Ali Fayez Alkoradees, Arpita, Aseel Smerat

    Published 2025-01-01
    “…Results obtained show that FATA consistently outperforms the other algorithms in terms of convergence and solution quality, offering a robust approach to solving single objective optimization problems. …”
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    Article
  6. 386

    Comparative analysis of principal modulation techniques for modular multilevel converter and a modified reduced switching frequency algorithm for nearest level pulse width modulati... by M. Benboukous, H. Bahri, M. Talea, M. Bour, K. Abdouni

    Published 2025-07-01
    “…The Modular Multilevel Converter (MMC) is an advanced topology widely used in medium and high-power applications, offering significant advantages over other multilevel converters, including high efficiency and superior output waveform quality. …”
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    Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study by Yuan Liu, Songyun Zhao, Wenyi Du, Wei Shen, Ning Zhou

    Published 2025-01-01
    “…Additionally, calibration curves, decision curve analysis (DCA), and external validation were integrated to provide a comprehensive evaluation of the model’s clinical applicability and utility.ResultsAmong the four predictive models, the XGBoost algorithm demonstrated superior performance. …”
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    Article
  9. 389

    Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

    Published 2025-06-01
    “…In addition to eliminating waste in manufacturing resources, it also evaluates the impact of these improvements on sustainability. …”
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    Article
  10. 390

    Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

    Published 2024-12-01
    “…Its performance in predicting various water quality indicators is then evaluated. The results show that the RFR model exhibits excellent performance, achieving high levels of prediction accuracy and stability for all indicators. …”
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    Article
  11. 391

    Optimizing Rotary Cement Kiln modelling: A comparative analysis of metaheuristics in a real-world application by Miguel Ángel Castán-Lascorz, Antonio Alcaide-Moreno, Jorge Arroyo

    Published 2025-03-01
    “…To address these challenges, this work evaluates the performance of five state-of-the-art metaheuristics and examines the impact of two penalty methods, death and static, on solution quality, constrained by a limited number of model evaluations due to time constraints. …”
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    Enhanced Curvature-Based Fabric Defect Detection: A Experimental Study with Gabor Transform and Deep Learning by Mehmet Erdogan, Mustafa Dogan

    Published 2024-11-01
    “…This method is particularly efficient due to its low data storage requirements and minimal processing time, making it ideal for real-time applications. Furthermore, we implemented and evaluated several other methods from the literature, including Gabor and Convolutional Neural Networks (CNNs), within a unified coding framework. …”
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  14. 394

    Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola, Antonino Tuttolomondo

    Published 2025-06-01
    “…AI, particularly machine learning and deep learning algorithms, has emerged as a transformative tool to address these challenges by automating image acquisition, optimizing signal quality, and enhancing diagnostic accuracy. …”
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    Article
  15. 395

    Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid by Emmanuel Ogbodo, David Dorrell, Adnan Abu-Mahfouz

    Published 2021-07-01
    “…The quality of service metrics used for evaluating the performance are the end-to-end delay, bit error rate, and energy consumption. …”
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    Translational analysis of data science and causal learning in real-world clinical evaluation of traditional Chinese medicine by Wei Yang, Danhui Yi, XiaoHua Zhou, Yuanming Leng

    Published 2024-03-01
    “…The methodology involves several key steps, including data integration and warehouse building, high-dimensional feature selection, the use of interpretable statistical machine learning algorithms, complex networks, and graph network analysis, knowledge mining techniques such as natural language processing and machine learning, observational study design, and the application of artificial intelligence tools to build an intelligent engine for translational analysis. …”
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